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GPU Fingerprinting Can Be Used to Track You Online: Researchers

An international team of researchers from France, Israel and Australia have developed a new technique that can identify individual users according to their specific, unique graphics card signature. Named Drawn Apart, the research, which serves as a proof of concept, serves as a warning towards more invasive identification measures that websites or ill-intentioned actors could take in order to collect data on individual users’ online activities in real-time.

The technique is based on the inherent variations of hardware due to variability in manufacturing processes and individual components. Much like no human fingerprint is identical to another, no single CPU, GPU, or any other consumer item is identical to one another. This is part of the reason why CPU and GPU overclocking varies even within the same product model from manufacturers, and gave rise to the emergence of said “golden” hardware. This, in turn, means that there are minute, individual variations on performance, power, and processing capabilities of each graphics card, making this kind of identification possible.

The GPU fingerprinting technique presented in a graphical view, showing that two otherwise identical GPUs produce different, individual results. This, in turn, can be attributed to a single users’ online activity. (Image credit:

The model created by the researchers makes use of fixed workloads based on WebGL (web Graphics Library), the cross-platform API that allows graphics cards to render graphics as their are presented in-browser. Through it, DrawnApart takes over 176 measurements across 16 data collection points by running vertex operations related to short GLSL (OpenGL Shading Language), which prevents workloads from being distributed across random work units – making the results repeatable and, as such, individual for each GPU. DrawnApart can then measure the time needed to complete vertex renders, handle stall functions, and other graphics-specific workloads.

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